Vivek Thazhathattil

Vivek Thazhathattil

Doctoral Student, Department of Aerospace Engineering
Indian Institute of Science, Bangalore

About

I am a Doctoral student at the Indian Institute of Science (IISc), Bangalore, specializing in Data-driven modelling and Complex systems theory within the Aerospace domain. I currently work in Combustion Physics Lab under the guidance of Prof. Santosh Hemchandra. My research focuses on uncovering the underlying physics of complex fluid flows through advanced computational methods and network theory.

I have extensive experience in high-performance computing, specifically developing and managing in-house CFD (LES/DNS) solvers primarily written in C. My technical contributions include implementing rotating overlapping meshes, periodic boundary conditions, and interfacing solvers with chemical kinetics libraries like Cantera.

Expertise

Aerospace & CFD

  • In-house LES/DNS Solver development (C)
  • Rotating & Overlapping Mesh implementation
  • Compressor Cascade & Turbomachinery flows
  • Aeroacoustic Source Localization
  • HPC Cluster Management

Data-driven flow analysis

  • Complex Network Analysis (CNA)
  • Information Theoretical methods
  • Linear Stability Analysis (LSA)
  • Data-driven Wavemaker Identification
  • Large-scale Flow Dataset Processing

Research

2026

Unsteady Wake Dynamics in Multi-Cylinder Arrays

Using Large-Eddy Simulation (LES) at Re = 10,000 to determine flow evolution past side-by-side cylinders. Complex network analysis identifies the location and spatial extent of flow regions governing unsteady wake dynamics, distinguishing between asymmetric gap flows and symmetric shedding patterns.

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2024

Aeroacoustic Source Localization in Turbulent Jets

We propose a data-driven approach for noise source localization using Transfer Entropy (TE). Applied to a Mach 3.0 turbulent jet at Re = 7.5M, this information-theoretic measure helps identify acoustic sources corresponding to pressure oscillations, validated against experimental measurements and FW-H analogy predictions.

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2023 / 2024

Wavemaker Identification in Swirling Flows

The precessing vortex core (PVC) oscillation is a self-excited flow instability associated with vortex breakdown. We assess a data-driven approach using Complex Network Analysis (CNA) to identify critical regions driving unsteady dynamics of canonical flows. Networks constructed from LES velocity data use correlation and mutual information to identify network hubs, successfully characterizing internal feedback regions.

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